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High-resolution large-area digital orthophoto map generation using LROC NAC images / Kaichang Di in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 481 - 491 Titre : High-resolution large-area digital orthophoto map generation using LROC NAC images Type de document : Article/Communication Auteurs : Kaichang Di, Auteur ; Jia Mengna, Auteur ; Xin Xin, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 481 - 491 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage [Termes IGN] Chine [Termes IGN] compensation par bloc [Termes IGN] erreur de positionnement [Termes IGN] image à haute résolution [Termes IGN] Lune [Termes IGN] modèle géométrique de prise de vue [Termes IGN] modèle numérique de terrain [Termes IGN] orthoimage [Termes IGN] orthophotoplan numérique [Termes IGN] zone homogène Résumé : (auteur) The Chang'e-5 mission of China is planned to be launched in 2019 to the landing area near Mons Rümker located in Oceanus Procellarum. Aiming to generate a high-resolution and high-quality digital orthophoto map (DOM) of the planned landing area for supporting the mission and various scientific analyses, this study developed a systematic and effective method for large-area seamless DOM production. The mapping results of the Chang'e-5 landing area using over 700 Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images are presented. The resultant seamless DOM has a resolution of 1.5 m, covers a large area of 20° in longitude and 4° in latitude, and is tied to SLDEM2015. The results demonstrate that the proposed method can reduce the geometric inconsistencies among the LROC NAC images to the subpixel level and the positional errors with respect to the reference digital elevation model to about one grid cell size. Numéro de notice : A2019-257 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.481 Date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.481 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93052 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019071	SL	Revue	Centre de documentation	Revues en salle	Disponible

Occlusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 493 - 508 Titre : Occlusion probability in operational forest inventory field sampling with ForeStereo Type de document : Article/Communication Auteurs : Fernando Montes, Auteur ; Mariola Sánchez-González, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 493 - 508 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] biomasse forestière [Termes IGN] capteur optique [Termes IGN] couvert forestier [Termes IGN] détection d'arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] erreur systématique [Termes IGN] Espagne [Termes IGN] Fagus sylvatica [Termes IGN] gestion forestière [Termes IGN] image hémisphérique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle stéréoscopique [Termes IGN] Pinus sylvestris [Termes IGN] placette d'échantillonnage [Termes IGN] Pyrénées (montagne) [Termes IGN] volume en bois Résumé : (auteur) Field data in forest inventories are increasingly obtained using proximal sensing technologies, often under fixed-point sampling. Under fixed-point sampling some trees are not detected due to instrument bias and occlusions, hence involving an underestimation of the number of trees per hectare (N). The aim here is to evaluate various approaches to correct tree occlusions and instrument bias estimates calculated with data from ForeStereo (proximal sensor based on stereoscopic hemispherical images) under a fixed-point sampling strategy. Distance-sampling and the new hemispherical photogrammetric correction (HPC), which combines image segmentation-based correction for instrument bias with a novel approach for estimating the proportion of shadowed sampling area in stereoscopic hemispherical images, best estimated N and basal area (BA). Distance-sampling slightly overestimated N (11% bias, 0.60 Pearson coefficient with the reference measures) and BA (4%, 0.82). HPC provided less biased N estimates (-6%, 0.61) but underestimated BA (-8%, 0.83). HPC most accurately retrieved the diameter distribution. Numéro de notice : A2019-258 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.493 Date de publication en ligne : 07/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.493 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93060 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019071	SL	Revue	Centre de documentation	Revues en salle	Disponible

A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 509 - 520 Titre : A novel method for separating woody and herbaceous time series Type de document : Article/Communication Auteurs : Qiang Zhou, Auteur ; Shuguang Liu, Auteur ; Michael J Hill, Auteur Année de publication : 2019 Article en page(s) : pp 509 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Afrique australe [Termes IGN] bois [Termes IGN] extraction de la végétation [Termes IGN] image à haute résolution [Termes IGN] image Ikonos [Termes IGN] image Landsat-SWIR [Termes IGN] image Terra-MODIS [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] plante herbacée [Termes IGN] savane [Termes IGN] série temporelle [Termes IGN] variation saisonnière Résumé : (auteur) Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. Numéro de notice : A2019-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.509 Date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93062 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019071	SL	Revue	Centre de documentation	Revues en salle	Disponible